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Housing price forecastability: A factor analysis

Author

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  • Lasse Bork

    (Aalborg University)

  • Stig V. Møller

    (Aarhus University and CREATES)

Abstract

We examine US housing price forecastability using a common factor approach based on a large panel of 122 economic time series. We find that a simple three-factor model generates an explanatory power of about 50% in one-quarter ahead in-sample forecasting regressions. The predictive power of the model stays high at longer horizons. The estimated factors are strongly statistically signi?cant according to a bootstrap resampling method which takes into account that the factors are estimated regressors. The simple three-factor model also contains substantial out-of-sample predictive power and performs remarkably well compared to both autoregressive benchmarks and computational intensive forecast combination models.

Suggested Citation

  • Lasse Bork & Stig V. Møller, 2012. "Housing price forecastability: A factor analysis," CREATES Research Papers 2012-27, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2012-27
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    File URL: https://repec.econ.au.dk/repec/creates/rp/12/rp12_27.pdf
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    Cited by:

    1. Mehmet Balcilar & Elie Bouri & Rangan Gupta & Mark E. Wohar, 2018. "Mortgage Default Risks and High-Frequency Predictability of the US Housing Market: A Reconsideration," Working Papers 201875, University of Pretoria, Department of Economics.
    2. repec:ipg:wpaper:2014-585 is not listed on IDEAS
    3. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
    4. Taufiq Choudhry, 2020. "Economic Policy Uncertainty and House Prices: Evidence from Geographical Regions of England and Wales," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 48(2), pages 504-529, June.
    5. Oguzhan Cepni & Rangan Gupta & Yigit Onay, 2022. "The role of investor sentiment in forecasting housing returns in China: A machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1725-1740, December.
    6. Theodore Panagiotidis & Panagiotis Printzis, 2016. "On the macroeconomic determinants of the housing market in Greece: a VECM approach," International Economics and Economic Policy, Springer, vol. 13(3), pages 387-409, July.
    7. Paul E. Carrillo & Eric R. Wit & William Larson, 2015. "Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the United States and the Netherlands," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 43(3), pages 609-651, September.
    8. Paul E. Carrillo & Erik Robert De Wit & William D. Larson, 2012. "Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the U.S. and the Netherlands," Working Papers 2012-11, The George Washington University, Institute for International Economic Policy.
    9. George Milunovich, 2020. "Forecasting Australia's real house price index: A comparison of time series and machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1098-1118, November.
    10. Christou, Christina & Gupta, Rangan & Hassapis, Christis, 2017. "Does economic policy uncertainty forecast real housing returns in a panel of OECD countries? A Bayesian approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 50-60.
    11. Tripathi, Sabyasachi, 2019. "Macroeconomic Determinants of Housing Prices: A Cross Country Level Analysis," MPRA Paper 98089, University Library of Munich, Germany.
    12. Bork, Lasse & Møller, Stig V., 2015. "Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection," International Journal of Forecasting, Elsevier, vol. 31(1), pages 63-78.
    13. Stig Vinther Møller & Thomas Pedersen & Erik Christian Montes Schütte & Allan Timmermann, 2024. "Search and Predictability of Prices in the Housing Market," Management Science, INFORMS, vol. 70(1), pages 415-438, January.
    14. Stig Vinther Møller & Thomas Pedersen & Erik Christian Montes Schütte & Allan Timmermann, 2024. "Search and Predictability of Prices in the Housing Market," Management Science, INFORMS, vol. 70(1), pages 415-438, January.
    15. Kucharska-Stasiak Ewa, 2019. "Valuation Schools and the Evolution of the Income Approach. An Evaluation of Change Trends," Real Estate Management and Valuation, Sciendo, vol. 27(2), pages 66-76, June.
    16. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05r, Department of Economics, University of Birmingham.

    More about this item

    Keywords

    House prices; Forecasting; Factor model; Principal components; Macroeconomic factors; Factor forecast combination; Bootstrap;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • G1 - Financial Economics - - General Financial Markets

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